Methodology of an Energy Efficient-Embedded Self-Adaptive Software Design for Multi-Cores and Frequency-Scaling Processors Used in Real-Time Systems

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@Article{ciopinski:2025:Electronics,

• author = "Leszek Ciopinski",
• title = "Methodology of an Energy Efficient-Embedded Self-Adaptive Software Design for Multi-Cores and Frequency-Scaling Processors Used in Real-Time Systems",
• journal = "Electronics",
• year = "2025",
• volume = "14",
• number = "3",
• pages = "Article No. 556",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2079-9292",
• URL = "https://www.mdpi.com/2079-9292/14/3/556",
• DOI = "doi:10.3390/electronics14030556",
• abstract = "In a kind of system, where strong time constraints exist, very often, worst-case design is applied. It could drive to the suboptimal usage of resources. In previous work, the mechanism of self-adaptive software that is able to reduce this was presented. This paper introduces a novel extension of the method for self-adaptive software synthesis applicable for real-time multicore embedded systems with dynamic voltage and frequency scaling (DVFS). It is based on a multi-criteria approach to task scheduling, optimising both energy consumption and proof against time delays. The method can be applied to a wide range of embedded systems, such as multimedia systems or Industrial Internet of Things (IIoT). The main aim of this research is to find the method of automatic construction of the task scheduler that is able to minimise energy consumption during the varying execution times of each task.",
• notes = "also known as \cite{electronics14030556}",

}

Genetic Programming entries for Leszek Ciopinski

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